A closer look at NFV execution models

Peng Zheng, Arvind Narayanan, Zhi Li Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Network Function Virtualization (NFV) advocates running service function chains (SFCs) on commodity servers as software, thereby providing a new level of flexibility to the deployment and management of network services. However, as we move from 10/40 Gbps to 100/400 Gbps line rates, it is challenging to build an NF execution framework that can deliver high performance at the maximum line speed using commodity servers, while providing scalability and flexibility afforded by software. In this paper, we investigate a fundamental problem of any NFV framework, i.e. how to execute SFCs on commodity servers by examining and comparing the performance of two execution models: the pipeline and run-to-completion models. In particular, we investigate how the multi-core server architecture affects the performance of SFC execution models by conducting extensive experiments on a testbed and shed new insights on the design and optimization of SFC execution models.

Original languageEnglish (US)
Title of host publicationAPNet 2019 - Proceedings of the 2019 Asia-Pacific Workshop on Networking
PublisherAssociation for Computing Machinery
Pages85-91
Number of pages7
ISBN (Electronic)9781450376358
DOIs
StatePublished - Aug 17 2019
Event3rd ACM SIGCOMM Asia-Pacific Workshop on Networking, APNet 2019 - Beijing, China
Duration: Aug 17 2019Aug 18 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference3rd ACM SIGCOMM Asia-Pacific Workshop on Networking, APNet 2019
CountryChina
CityBeijing
Period8/17/198/18/19

Keywords

  • Execution model
  • Hybrid
  • Multi-core
  • NFV
  • NUMA
  • Pipeline
  • Run-to-completion

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  • Cite this

    Zheng, P., Narayanan, A., & Zhang, Z. L. (2019). A closer look at NFV execution models. In APNet 2019 - Proceedings of the 2019 Asia-Pacific Workshop on Networking (pp. 85-91). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3343180.3343188